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A Homogeneous Catalog of Oscillating Solar-Type Stars Observed by the Kepler Mission and a New Amplitude Scaling Relation Including Chromospheric Activity

This paper presents the largest homogeneous catalog to date of 765 Kepler main-sequence and subgiant stars, featuring re-analyzed asteroseismic parameters, 50 new detections, and a novel amplitude scaling relation that incorporates chromospheric activity to predict oscillation amplitudes with high precision.

Original authors: Maryum Sayeed, Daniel Huber, Ashley Chontos, Yaguang Li

Published 2026-04-20

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CC BY 4.0

Original authors: Maryum Sayeed, Daniel Huber, Ashley Chontos, Yaguang Li

Original paper licensed under CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

Imagine the universe as a giant, cosmic orchestra. Most stars are like steady drummers, beating a rhythm that we can't hear. But some stars, including our Sun, are like violins—they vibrate and "ring" with sound waves trapped inside them. This phenomenon is called asteroseismology (star-quakes). By listening to these vibrations, astronomers can figure out a star's age, size, and mass, just like a doctor uses an ultrasound to see inside a human body.

This paper is essentially a giant, high-quality catalog of these cosmic "ringing" stars, created by re-examining data from NASA's famous Kepler Mission.

Here is the breakdown of what the researchers did, using some everyday analogies:

1. The Great "Remastering" Project

Think of the Kepler mission as a recording studio that captured thousands of hours of star music. Over the years, the studio released different versions of the recordings. The researchers in this paper took all the available "short-cadence" recordings (which are like high-definition, fast-sampling audio files needed to catch the quick vibrations of smaller, Sun-like stars) and ran them through a new, automated software tool called pySYD.

The Analogy: Imagine you have an old, slightly blurry photo album of your family. You take all the photos and run them through a modern AI photo-enhancer. Suddenly, faces you couldn't see before become clear, and you spot people you missed entirely.
The Result: They found 50 new stars that were "ringing" but had been missed in previous studies. They also confirmed 715 others, creating a total catalog of 765 stars.

2. The "Star ID Card"

For every one of these 765 stars, the team created a detailed ID card. They measured two main things:

$\nu_{max}$ (Nu-max): How fast the star is vibrating at its loudest point.
$\Delta\nu$ (Delta-nu): The spacing between the different notes the star plays.

Using these "notes," they calculated the star's mass (how heavy it is) and radius (how big it is) with incredible precision.

The Analogy: It's like listening to a bell. If you know the pitch and the spacing of the overtones, you can tell exactly how big the bell is and what metal it's made of, without ever touching it.
The Accuracy: Their size estimates were off by less than 3% (like guessing a person's height and being off by only an inch), and their weight estimates were off by about 10%.

3. The "Activity" Factor (The Noisy Neighbor)

One of the biggest discoveries in this paper is about stellar activity. Stars, like the Sun, have sunspots and magnetic storms. The researchers found that when a star is very "active" (like a teenager with too much energy), its vibrations get quieter.

The Analogy: Imagine trying to hear a quiet violin in a room. If the room is silent, you hear it perfectly. But if someone starts banging on pots and pans (stellar activity), the violin gets drowned out.
The New Formula: The team created a new math formula that includes an "activity meter." Now, when they predict how loud a star should be ringing, they can factor in how "noisy" the star's surface is. This makes their predictions much more accurate.

4. The Planet Hunters

About 100 of these stars are known to have planets orbiting them. By getting the star's size so precisely, the team could also calculate the size of the planets orbiting them more accurately.

The Analogy: If you know the exact size of a stage (the star), you can figure out exactly how big the actor (the planet) is when they walk in front of it and block the light.
The Discovery: They found that the sizes of these planets fit perfectly into a known pattern called the "radius valley," which helps explain how planets form and evolve.

5. Why This Matters

This paper is the "Gold Standard" reference for studying Sun-like stars.

For the Future: As new telescopes (like TESS and the upcoming PLATO mission) look at millions of stars, scientists will use this catalog as a training manual to understand them.
For Time Travel: By knowing the exact size and mass of these stars, astronomers can estimate their ages. This helps us understand how the galaxy has changed over billions of years.

In a nutshell: The authors took a massive pile of old star data, cleaned it up with new tools, found 50 new "singing" stars, figured out exactly how big and heavy they are, and discovered that a star's "mood" (activity level) changes how loud it sings. This gives us a much clearer picture of the life cycle of stars like our Sun.

1. Problem Statement

While asteroseismology has revolutionized the study of stellar interiors, previous catalogs of solar-like oscillators in the Kepler mission often suffered from heterogeneity due to the use of different analysis pipelines and data processing methods. This led to systematic offsets in derived stellar parameters (mass, radius, age) across the Hertzsprung–Russell diagram. Furthermore, the relationship between stellar activity and the suppression of oscillation amplitudes had not been rigorously quantified or incorporated into amplitude scaling relations. Additionally, there was a need for a comprehensive, re-analyzed catalog of main-sequence and subgiant stars observed in Kepler's short-cadence mode (58.5s), which is required to detect oscillations in these stars but was only available for a pre-selected subset of targets.

2. Methodology

The authors employed a unified, automated approach to re-analyze Kepler data:

Data Selection: The study started with 5,678 unique Kepler stars observed in short-cadence. After filtering out eclipsing binaries, $\delta$ Scuti pulsators, and stars with known long-cadence detections, 4,346 targets remained. This included a systematic search of 766 exoplanet host candidates.
Pipeline (pySYD): The authors used pySYD, an open-source Python pipeline adapted from the IDL-based SYD pipeline. This tool automates the extraction of global asteroseismic parameters:
- Identification of the power excess due to solar-like oscillations.
- Optimization and correction of the stellar background (granulation and activity) using Harvey models.
- Calculation of the frequency of maximum power ( $\nu_{\max}$ ) and the average large frequency separation ( $\Delta\nu$ ).
Data Preparation: Light curves were processed using lightkurve, including sigma-clipping, Savitzky-Golay smoothing to remove low-frequency trends, and the generation of critically sampled power density spectra. Special handling was applied to specific targets with known data quality issues or mixed-mode complexities.
Activity Indicators: To study amplitude suppression, the authors derived chromospheric activity indices ( $\log R'_{HK}$ ) from Keck/HIRES spectroscopic data, utilizing the $S_{HK}$ index and converting it to $\log R'_{HK}$ using stellar parameters ( $T_{\text{eff}}$ , $\log g$ , [Fe/H]).
Stellar Parameter Derivation: Radii and masses were calculated using standard asteroseismic scaling relations combined with effective temperatures from Berger et al. (2020b).

3. Key Contributions

Homogeneous Catalog: The creation of the largest and most homogeneous catalog to date for Kepler main-sequence and subgiant stars, containing 765 stars with detected oscillations.
New Detections: Identification of 50 new oscillating stars, seven of which are confirmed or candidate exoplanet hosts.
Activity-Dependent Scaling Relation: The derivation of a new amplitude scaling relation that explicitly includes a term for chromospheric activity ( $\log R'_{HK}$ ), addressing a gap in previous models.
Exoplanet Host Characterization: The catalog includes 101 planet-hosting stars, allowing for the re-calculation of planetary radii using precise seismic stellar radii.

4. Key Results

Asteroseismic Parameters and Precision

Measurements: The catalog provides $\nu_{\max}$ and $\Delta\nu$ with median uncertainties of 3.4% and 1.9%, respectively.
Stellar Parameters: Derived radii and masses have average precisions of 2.7% and 10.4%.
Validation:
- Comparison with literature values shows excellent agreement: average offsets of $0.2 \pm 0.4\%$ for $\nu_{\max}$ and $0.2 \pm 0.7\%$ for $\Delta\nu$ .
- Seismic radii agree with Gaia parallaxes (from Berger et al. 2020b) with a mean offset of $0.8 \pm 0.2\%$ and a scatter of 6%.
- Seismic masses show a systematic offset of $\sim6\%$ compared to Gaia isochrone masses, likely due to uncertainties in isochrone fitting rather than seismic errors.

Amplitude Scaling Relation

Activity Term: The authors derived a modified scaling relation:
$\frac{A}{A_\odot} = L_s \left(\frac{\log R'_{HK}}{\log R'_{HK,\odot}}\right)^u M^t T_{\text{eff}}^{r-1} c_K(T_{\text{eff}})$
where $u \approx 3.1$ .
Performance: Including the activity term reduced the scatter in predicted amplitudes from 12% (using the Huber et al. 2011 relation) to 8–9%. The Bayesian Information Criterion (BIC) strongly favors the new model with the activity term.
Implication: Stellar activity is a dominant factor in amplitude suppression, and including it significantly improves amplitude predictions.

Exoplanet Hosts and Planetary Radii

New Hosts: Seven new Kepler planet hosts were discovered with oscillations (KOIs 1032, 302, 126, 94, 684, 76, 2533).
Radius Valley: Re-calculated planet radii using seismic stellar radii confirmed the "radius valley" (a gap in planet sizes around $1.8 R_\oplus$ ) with high precision. The mean offset between these new radii and previous estimates (Van Eylen et al. 2018) is only $1.4 \pm 0.4\%$ .

Gyrochronology and Rotation

The catalog includes rotation periods for 451 stars.
Only 11 stars have sufficiently high signal-to-noise and resolution for detailed mode modeling to determine ages, highlighting the need for higher-quality data for precise gyrochronology in evolved stars.

5. Significance

Benchmarking: This catalog serves as a critical benchmark for calibrating indirect methods of determining stellar parameters and for testing data analysis tools.
Future Missions: The findings regarding activity-dependent amplitude scaling are crucial for the upcoming PLATO and Nancy Grace Roman missions, which will observe millions of stars. Understanding how activity suppresses amplitudes will improve the yield and accuracy of asteroseismic detections in these future surveys.
Stellar Physics: The work provides the most robust dataset to date for studying the interplay between stellar activity, magnetic fields, and oscillation amplitudes in solar-type stars, resolving discrepancies in previous heterogeneous catalogs.